Tests for gene‐environment interaction from case‐control data: a novel study of type I error, power and designs

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Abstract
To evaluate the risk of a disease associated with the joint effects of genetic susceptibility and environmental exposures, epidemiologic researchers often test for non‐multiplicative gene‐environment effects from case‐control studies. In this article, we present a comparative study of four alternative tests for interactions: (i) the standard case‐control method; (ii) the case‐only method, which requires an assumption of gene‐environment independence for the underlying population; (iii) a two‐step method that decides between the case‐only and case‐control estimators depending on a statistical test for the gene‐environment independence assumption and (iv) a novel empirical‐Bayes (EB) method that combines the case‐control and case‐only estimators depending on the sample size and strength of the gene‐environment association in the data. We evaluate the methods in terms of integrated Type I error and power, averaged with respect to varying scenarios for gene‐environment association that are likely to appear in practice. These unique studies suggest that the novel EB procedure overall is a promising approach for detection of gene‐environment interactions from case‐control studies. In particular, the EB procedure, unlike the case‐only or two‐step methods, can closely maintain a desired Type I error under realistic scenarios of gene‐environment dependence and yet can be substantially more powerful than the traditional case‐control analysis when the gene‐environment independence assumption is satisfied, exactly or approximately. Our studies also reveal potential utility of some non‐traditional case‐control designs that samples controls at a smaller rate than the cases. Apart from the simulation studies, we also illustrate the different methods by analyzing interactions of two commonly studied genes, N‐acetyl transferase type 2 and glutathione s‐transferase M1, with smoking and dietary exposures, in a large case‐control study of colorectal cancer. Genet. Epidemiol. 2008. Published 2008 Wiley‐Liss, Inc.